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I mean, it's a structured output model that (apparently) can't hallucinate. I don't mind the name.

It can't hallucinate, but it doesn't mean it can't make wrong decisions. Just because it adheres to a specific output format at all time, while LLMs have the output format at their mercy, then the claim of not hallucinating is made technically true.

I think that this specific part is not super interesting if your harness just recovers from invalid LLM outputs.

The latency and cost - yes, those are super interesting.

You can get rigid output format from "classic" LLMs https://docs.vllm.ai/en/latest/features/structured_outputs/ though model support is limited.

Would like to have something like in the original post but open weights.

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